tensorflow TF2.0：转换模型：恢复保存的模型时出错：检查点(根)中存在未解析的对象,optimizer.iter：属性

envsm3lx  于 2022-12-04  发布在  其他
关注(0)|答案(4)|浏览(436)

我正在尝试恢复检查点并对不同的句子NMT Attention Model进行预测。在恢复检查点和预测时，我得到了乱码的结果，并显示以下警告：

Unresolved object in checkpoint (root).optimizer.iter: attributes {
  name: "VARIABLE_VALUE"
  full_name: "Adam/iter"
  checkpoint_key: "optimizer/iter/.ATTRIBUTES/VARIABLE_VALUE"
}

下面是我收到的其他警告和结果：

WARNING: Logging before flag parsing goes to stderr.
W1008 09:57:52.766877 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer.iter
W1008 09:57:52.767037 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer.beta_1
W1008 09:57:52.767082 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer.beta_2
W1008 09:57:52.767120 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer.decay
W1008 09:57:52.767155 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer.learning_rate
W1008 09:57:52.767194 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.embedding.embeddings
W1008 09:57:52.767228 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.gru.state_spec
W1008 09:57:52.767262 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.fc.kernel
W1008 09:57:52.767296 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.fc.bias
W1008 09:57:52.767329 4594230720 util.py:244] Unresolved object in checkpoint: (root).encoder.embedding.embeddings
W1008 09:57:52.767364 4594230720 util.py:244] Unresolved object in checkpoint: (root).encoder.gru.state_spec
W1008 09:57:52.767396 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.gru.cell.kernel
W1008 09:57:52.767429 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.gru.cell.recurrent_kernel
W1008 09:57:52.767461 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.gru.cell.bias
W1008 09:57:52.767493 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.attention.W1.kernel
W1008 09:57:52.767526 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.attention.W1.bias
W1008 09:57:52.767558 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.attention.W2.kernel
W1008 09:57:52.767590 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.attention.W2.bias
W1008 09:57:52.767623 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.attention.V.kernel
W1008 09:57:52.767657 4594230720 util.py:244] Unresolved object in checkpoint: (root).decoder.attention.V.bias
W1008 09:57:52.767688 4594230720 util.py:244] Unresolved object in checkpoint: (root).encoder.gru.cell.kernel
W1008 09:57:52.767721 4594230720 util.py:244] Unresolved object in checkpoint: (root).encoder.gru.cell.recurrent_kernel
W1008 09:57:52.767755 4594230720 util.py:244] Unresolved object in checkpoint: (root).encoder.gru.cell.bias
W1008 09:57:52.767786 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.embedding.embeddings
W1008 09:57:52.767818 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.fc.kernel
W1008 09:57:52.767851 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.fc.bias
W1008 09:57:52.767884 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).encoder.embedding.embeddings
W1008 09:57:52.767915 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.gru.cell.kernel
W1008 09:57:52.767949 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.gru.cell.recurrent_kernel
W1008 09:57:52.767981 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.gru.cell.bias
W1008 09:57:52.768013 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.attention.W1.kernel
W1008 09:57:52.768044 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.attention.W1.bias
W1008 09:57:52.768077 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.attention.W2.kernel
W1008 09:57:52.768109 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.attention.W2.bias
W1008 09:57:52.768143 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.attention.V.kernel
W1008 09:57:52.768175 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).decoder.attention.V.bias
W1008 09:57:52.768207 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).encoder.gru.cell.kernel
W1008 09:57:52.768239 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).encoder.gru.cell.recurrent_kernel
W1008 09:57:52.768271 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).encoder.gru.cell.bias
W1008 09:57:52.768303 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.embedding.embeddings
W1008 09:57:52.768335 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.fc.kernel
W1008 09:57:52.768367 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.fc.bias
W1008 09:57:52.768399 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).encoder.embedding.embeddings
W1008 09:57:52.768431 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.gru.cell.kernel
W1008 09:57:52.768463 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.gru.cell.recurrent_kernel
W1008 09:57:52.768495 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.gru.cell.bias
W1008 09:57:52.768527 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.attention.W1.kernel
W1008 09:57:52.768559 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.attention.W1.bias
W1008 09:57:52.768591 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.attention.W2.kernel
W1008 09:57:52.768623 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.attention.W2.bias
W1008 09:57:52.768654 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.attention.V.kernel
W1008 09:57:52.768686 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).decoder.attention.V.bias
W1008 09:57:52.768718 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).encoder.gru.cell.kernel
W1008 09:57:52.768750 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).encoder.gru.cell.recurrent_kernel
W1008 09:57:52.768782 4594230720 util.py:244] Unresolved object in checkpoint: (root).optimizer's state 'v' for (root).encoder.gru.cell.bias
W1008 09:57:52.768816 4594230720 util.py:252] A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issues. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check explicit. See https://www.tensorflow.org/alpha/guide/checkpoints#loading_mechanics for details.
Input: <start> hola <end>
Predicted translation: ? attack now relax hello

最后的警告说：
“已恢复检查点（例如tf.train.Checkpoint.restore或tf.keras.Model.load_weights），但未使用所有检查点值...”这意味着什么？

tensorflow

4条答案

按热度按时间
uqdfh47h

uqdfh47h1#

这意味着您没有使用已恢复的所有检查点值。
发生这种情况的原因是，您正在还原具有定型信息（如优化程序变量）的模型，但您仅将其用于预测，而不是定型。在预测时，您不需要保存的优化程序值，这就是程序告诉您未使用这些值的原因。
如果您使用这个还原的模型来训练新数据，这个警告就会消失。
您可以使用model.load_weights(...).expect_partial()或tf.train.Checkpoint.restore(...).expect_partial()使这些警告静音。
更好的解决方案是在训练时只保存推理所需的变量：

saver = tf.train.Saver(tf.model_variables())

tf.model_variables()是模型中用于推理的变量对象的子集（请参见tensorflow doc）。

赞(0）分享  回复(0）举报  2022-12-04
qoefvg9y

qoefvg9y2#

任何人在Tensorflow对象检测（工作解决方案）中遇到此错误要继续培训，请将pipeline.config中的num_steps值更新为比上一次运行更高的值：
原件：

num_steps: 25000
  optimizer {
    momentum_optimizer: {
      learning_rate: {
        cosine_decay_learning_rate {
          learning_rate_base: .04
          total_steps: 25000

更新日期：

num_steps: 50000
  optimizer {
    momentum_optimizer: {
      learning_rate: {
        cosine_decay_learning_rate {
          learning_rate_base: .04
          total_steps: 50000
赞(0）分享  回复(0）举报  2022-12-04
pdsfdshx

pdsfdshx3#

我使用了：tf.train.Checkpoint.restore（...）.expect_partial（）来恢复我的检查点，并将其用于推理。它对我很有效

赞(0）分享  回复(0）举报  2022-12-04
bq9c1y66

bq9c1y664#

model.load_weights(MY_CHECKPOINT_FILE).expect_partial()一直在为我工作

赞(0）分享  回复(0）举报  2022-12-04
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